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A New Approach to Estimating the Probability of Winning the Presidency

Author

Listed:
  • Edward H. Kaplan

    (Yale School of Management, Box 208200, New Haven, Connecticut 06520-8200)

  • Arnold Barnett

    (Sloan School of Management, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139)

Abstract

As the 2000 election so vividly showed, it is Electoral College standings rather than national popular votes that determine who becomes President. But current pre-election polls focus almost exclusively on the popular vote. Here we present a method by which pollsters can achieve both point estimates and margins of error for a presidential candidate's electoral-vote total. We use data from both the 2000 and 1988 elections to illustrate the approach. Moreover, we indicate that the sample sizes needed for reliable inferences are similar to those now used in popular-vote polling.

Suggested Citation

  • Edward H. Kaplan & Arnold Barnett, 2003. "A New Approach to Estimating the Probability of Winning the Presidency," Operations Research, INFORMS, vol. 51(1), pages 32-40, February.
    • Handle: RePEc:inm:oropre:v:51:y:2003:i:1:p:32-40
    DOI: 10.1287/opre.51.1.32.12794
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    Citations

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    Cited by:

    1. Ray C. Fair, 2004. "Predicting Electoral College Victory Probabilities from State Probability Data," Cowles Foundation Discussion Papers 1496, Cowles Foundation for Research in Economics, Yale University.
    2. Steven E. Rigdon & Jason J. Sauppe & Sheldon H. Jacobson, 2015. "Forecasting the 2012 and 2014 Elections Using Bayesian Prediction and Optimization," SAGE Open, , vol. 5(2), pages 21582440155, April.
    3. Ray Fair & Cowles Discussion & Yale Working, 2006. "Interpreting the Predictive Uncertainty of Elections," Yale School of Management Working Papers amz2643, Yale School of Management, revised 01 Aug 2007.
    4. Sebasti'an Morales & Charles Thraves, 2020. "On the Resource Allocation for Political Campaigns," Papers 2012.02856, arXiv.org.
    5. Edieal J. Pinker, 2013. "Introduction to the OR Forum Article: “Blotto Politics”," Operations Research, INFORMS, vol. 61(3), pages 531-531, June.
    6. Ray Fair & Cowles Discussion & Yale Working, 2006. "Interpreting the Predictive Uncertainty of Elections," Yale School of Management Working Papers amz2643, Yale School of Management, revised 01 Aug 2007.
    7. M. Keith Chen & Jonathan E. Ingersoll, Jr. & Edward H. Kaplan, 2008. "Modeling a Presidential Prediction Market," Management Science, INFORMS, vol. 54(8), pages 1381-1394, August.
    8. Ray C. Fair, 2006. "Interpreting the Predictive Uncertainty of Presidential Elections," Levine's Bibliography 321307000000000427, UCLA Department of Economics.
    9. Ray Fair, 2004. "Predicting Electoral College Victory Probabilities from State Probability Data," Yale School of Management Working Papers amz2406, Yale School of Management.
    10. Ray C. Fair, 2006. "Interpreting the Predictive Uncertainty of Elections," Cowles Foundation Discussion Papers 1579, Cowles Foundation for Research in Economics, Yale University, revised May 2007.
    11. Kevin Taaffe & Edwin Romeijn & Deepak Tirumalasetty, 2008. "A selective newsvendor approach to order management," Naval Research Logistics (NRL), John Wiley & Sons, vol. 55(8), pages 769-784, December.
    12. Ray Fair, 2004. "Predicting Electoral College Victory Probabilities from State Probability Data," Yale School of Management Working Papers amz2406, Yale School of Management.
    13. Sebastián Morales & Charles Thraves, 2021. "On the Resource Allocation for Political Campaigns," Production and Operations Management, Production and Operations Management Society, vol. 30(11), pages 4140-4159, November.

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